CHAPTER 1: INTRODUCTION
1.1. Report description
1.2. Key market segments
1.3. Key benefits to the stakeholders
1.4. Research methodology
1.4.1. Primary research
1.4.2. Secondary research
1.4.3. Analyst tools and models
CHAPTER 2: EXECUTIVE SUMMARY
2.1. CXO Perspective
CHAPTER 3: MARKET OVERVIEW
3.1. Market definition and scope
3.2. Key findings
3.2.1. Top impacting factors
3.2.2. Top investment pockets
3.3. Porter’s five forces analysis
3.3.1. Low bargaining power of suppliers
3.3.2. Low threat of new entrants
3.3.3. Low threat of substitutes
3.3.4. Low intensity of rivalry
3.3.5. Low bargaining power of buyers
3.4. Market dynamics
3.4.1. Drivers
3.4.1.1. Rise in demand for big data analytics
3.4.1.2. Enterprise-wide need for scalable and flexible database solutions
3.4.1.3. Growth in adoption of cloud computing technology
3.4.2. Restraints
3.4.2.1. High complexities to administrate NoSQL databases
3.4.2.2. Potential threat of data-related inconsistencies
3.4.3. Opportunities
3.4.3.1. Rise in adoption of advanced technologies such as AI and ML
CHAPTER 4: NOSQL MARKET, BY TYPE
4.1. Overview
4.1.1. Market size and forecast
4.2. Key-Value Store
4.2.1. Key market trends, growth factors and opportunities
4.2.2. Market size and forecast, by region
4.2.3. Market share analysis by country
4.3. Document Database
4.3.1. Key market trends, growth factors and opportunities
4.3.2. Market size and forecast, by region
4.3.3. Market share analysis by country
4.4. Column Based Store
4.4.1. Key market trends, growth factors and opportunities
4.4.2. Market size and forecast, by region
4.4.3. Market share analysis by country
4.5. Graph Database
4.5.1. Key market trends, growth factors and opportunities
4.5.2. Market size and forecast, by region
4.5.3. Market share analysis by country
CHAPTER 5: NOSQL MARKET, BY APPLICATION
5.1. Overview
5.1.1. Market size and forecast
5.2. Data Storage
5.2.1. Key market trends, growth factors and opportunities
5.2.2. Market size and forecast, by region
5.2.3. Market share analysis by country
5.3. Mobile Apps
5.3.1. Key market trends, growth factors and opportunities
5.3.2. Market size and forecast, by region
5.3.3. Market share analysis by country
5.4. Data Analytics
5.4.1. Key market trends, growth factors and opportunities
5.4.2. Market size and forecast, by region
5.4.3. Market share analysis by country
5.5. Web Apps
5.5.1. Key market trends, growth factors and opportunities
5.5.2. Market size and forecast, by region
5.5.3. Market share analysis by country
5.6. Others
5.6.1. Key market trends, growth factors and opportunities
5.6.2. Market size and forecast, by region
5.6.3. Market share analysis by country
CHAPTER 6: NOSQL MARKET, BY INDUSTRY VERTICAL
6.1. Overview
6.1.1. Market size and forecast
6.2. Retail
6.2.1. Key market trends, growth factors and opportunities
6.2.2. Market size and forecast, by region
6.2.3. Market share analysis by country
6.3. Gaming
6.3.1. Key market trends, growth factors and opportunities
6.3.2. Market size and forecast, by region
6.3.3. Market share analysis by country
6.4. IT
6.4.1. Key market trends, growth factors and opportunities
6.4.2. Market size and forecast, by region
6.4.3. Market share analysis by country
6.5. Others
6.5.1. Key market trends, growth factors and opportunities
6.5.2. Market size and forecast, by region
6.5.3. Market share analysis by country
CHAPTER 7: NOSQL MARKET, BY REGION
7.1. Overview
7.1.1. Market size and forecast By Region
7.2. North America
7.2.1. Key market trends, growth factors and opportunities
7.2.2. Market size and forecast, by Type
7.2.3. Market size and forecast, by Application
7.2.4. Market size and forecast, by Industry Vertical
7.2.5. Market size and forecast, by country
7.2.5.1. U.S.
7.2.5.1.1. Market size and forecast, by Type
7.2.5.1.2. Market size and forecast, by Application
7.2.5.1.3. Market size and forecast, by Industry Vertical
7.2.5.2. Canada
7.2.5.2.1. Market size and forecast, by Type
7.2.5.2.2. Market size and forecast, by Application
7.2.5.2.3. Market size and forecast, by Industry Vertical
7.3. Europe
7.3.1. Key market trends, growth factors and opportunities
7.3.2. Market size and forecast, by Type
7.3.3. Market size and forecast, by Application
7.3.4. Market size and forecast, by Industry Vertical
7.3.5. Market size and forecast, by country
7.3.5.1. UK
7.3.5.1.1. Market size and forecast, by Type
7.3.5.1.2. Market size and forecast, by Application
7.3.5.1.3. Market size and forecast, by Industry Vertical
7.3.5.2. Germany
7.3.5.2.1. Market size and forecast, by Type
7.3.5.2.2. Market size and forecast, by Application
7.3.5.2.3. Market size and forecast, by Industry Vertical
7.3.5.3. France
7.3.5.3.1. Market size and forecast, by Type
7.3.5.3.2. Market size and forecast, by Application
7.3.5.3.3. Market size and forecast, by Industry Vertical
7.3.5.4. Italy
7.3.5.4.1. Market size and forecast, by Type
7.3.5.4.2. Market size and forecast, by Application
7.3.5.4.3. Market size and forecast, by Industry Vertical
7.3.5.5. Spain
7.3.5.5.1. Market size and forecast, by Type
7.3.5.5.2. Market size and forecast, by Application
7.3.5.5.3. Market size and forecast, by Industry Vertical
7.3.5.6. Rest of Europe
7.3.5.6.1. Market size and forecast, by Type
7.3.5.6.2. Market size and forecast, by Application
7.3.5.6.3. Market size and forecast, by Industry Vertical
7.4. Asia-Pacific
7.4.1. Key market trends, growth factors and opportunities
7.4.2. Market size and forecast, by Type
7.4.3. Market size and forecast, by Application
7.4.4. Market size and forecast, by Industry Vertical
7.4.5. Market size and forecast, by country
7.4.5.1. China
7.4.5.1.1. Market size and forecast, by Type
7.4.5.1.2. Market size and forecast, by Application
7.4.5.1.3. Market size and forecast, by Industry Vertical
7.4.5.2. India
7.4.5.2.1. Market size and forecast, by Type
7.4.5.2.2. Market size and forecast, by Application
7.4.5.2.3. Market size and forecast, by Industry Vertical
7.4.5.3. Japan
7.4.5.3.1. Market size and forecast, by Type
7.4.5.3.2. Market size and forecast, by Application
7.4.5.3.3. Market size and forecast, by Industry Vertical
7.4.5.4. Australia
7.4.5.4.1. Market size and forecast, by Type
7.4.5.4.2. Market size and forecast, by Application
7.4.5.4.3. Market size and forecast, by Industry Vertical
7.4.5.5. South Korea
7.4.5.5.1. Market size and forecast, by Type
7.4.5.5.2. Market size and forecast, by Application
7.4.5.5.3. Market size and forecast, by Industry Vertical
7.4.5.6. Rest of Asia-Pacific
7.4.5.6.1. Market size and forecast, by Type
7.4.5.6.2. Market size and forecast, by Application
7.4.5.6.3. Market size and forecast, by Industry Vertical
7.5. LAMEA
7.5.1. Key market trends, growth factors and opportunities
7.5.2. Market size and forecast, by Type
7.5.3. Market size and forecast, by Application
7.5.4. Market size and forecast, by Industry Vertical
7.5.5. Market size and forecast, by country
7.5.5.1. Latin America
7.5.5.1.1. Market size and forecast, by Type
7.5.5.1.2. Market size and forecast, by Application
7.5.5.1.3. Market size and forecast, by Industry Vertical
7.5.5.2. Middle East
7.5.5.2.1. Market size and forecast, by Type
7.5.5.2.2. Market size and forecast, by Application
7.5.5.2.3. Market size and forecast, by Industry Vertical
7.5.5.3. Africa
7.5.5.3.1. Market size and forecast, by Type
7.5.5.3.2. Market size and forecast, by Application
7.5.5.3.3. Market size and forecast, by Industry Vertical
CHAPTER 8: COMPETITIVE LANDSCAPE
8.1. Introduction
8.2. Top winning strategies
8.3. Product mapping of top 10 player
8.4. Competitive dashboard
8.5. Competitive heatmap
8.6. Top player positioning, 2022
CHAPTER 9: COMPANY PROFILES
9.1. Aerospike Inc.
9.1.1. Company overview
9.1.2. Key executives
9.1.3. Company snapshot
9.1.4. Operating business segments
9.1.5. Product portfolio
9.1.6. Key strategic moves and developments
9.2. Couchbase Inc.
9.2.1. Company overview
9.2.2. Key executives
9.2.3. Company snapshot
9.2.4. Operating business segments
9.2.5. Product portfolio
9.2.6. Business performance
9.2.7. Key strategic moves and developments
9.3. IBM Corporation
9.3.1. Company overview
9.3.2. Key executives
9.3.3. Company snapshot
9.3.4. Operating business segments
9.3.5. Product portfolio
9.3.6. Business performance
9.3.7. Key strategic moves and developments
9.4. Neo4j, Inc.
9.4.1. Company overview
9.4.2. Key executives
9.4.3. Company snapshot
9.4.4. Operating business segments
9.4.5. Product portfolio
9.5. Objectivity, Inc
9.5.1. Company overview
9.5.2. Key executives
9.5.3. Company snapshot
9.5.4. Operating business segments
9.5.5. Product portfolio
9.6. Oracle Corporation
9.6.1. Company overview
9.6.2. Key executives
9.6.3. Company snapshot
9.6.4. Operating business segments
9.6.5. Product portfolio
9.6.6. Business performance
9.6.7. Key strategic moves and developments
9.7. Progress Software Corporation
9.7.1. Company overview
9.7.2. Key executives
9.7.3. Company snapshot
9.7.4. Operating business segments
9.7.5. Product portfolio
9.7.6. Business performance
9.7.7. Key strategic moves and developments
9.8. Riak
9.8.1. Company overview
9.8.2. Key executives
9.8.3. Company snapshot
9.8.4. Operating business segments
9.8.5. Product portfolio
9.9. ScyllaDB, Inc.
9.9.1. Company overview
9.9.2. Key executives
9.9.3. Company snapshot
9.9.4. Operating business segments
9.9.5. Product portfolio
9.9.6. Key strategic moves and developments
9.10. The Apache Software Foundation
9.10.1. Company overview
9.10.2. Key executives
9.10.3. Company snapshot
9.10.4. Operating business segments
9.10.5. Product portfolio
9.10.6. Business performance
| ※参考情報 NoSQLとは、「Not Only SQL」の略称で、従来のリレーショナルデータベース管理システム（RDBMS）とは異なるデータストレージの方法を指します。NoSQLデータベースは、特に大規模なデータ、分散型のアプリケーション、高速なデータ処理が求められる場合に適しています。従来のSQLデータベースでは、テーブルを基にしたデータ構造が求められますが、NoSQLでは柔軟性があり、様々なデータ形式を扱うことが可能です。 NoSQLデータベースは、大きく分けて4つのカテゴリに分類されます。まず、キーバリュー型データベースがあります。これは、データをキーとバリューのペアで格納し、簡単にデータの取得ができるという特徴があります。代表的な例としては、RedisやDynamoDBが挙げられます。次に、ドキュメント指向データベースがあります。これは、JSONやXMLなどの形式でデータを格納し、構造化されたデータを扱うことができます。MongoDBやCouchDBがこのカテゴリに属します。 三つ目のカテゴリーはカラム指向データベースです。これは、データをカラム単位で保存する方式で、高速な読み取り性能を持ちます。これにより、特に分析用途において効率が良くなります。CassandraやHBaseがこれに該当します。そして最後に、グラフ型データベースがあります。これは、データ同士の関係を持つグラフ構造で表現し、複雑なリレーションシップを管理するのに適しています。Neo4jやAmazon Neptuneが例として挙げられます。 NoSQLデータベースの用途は非常に多岐にわたります。例えば、大規模なWebアプリケーションやモバイルアプリケーションのバックエンドとして、リアルタイム分析、ビッグデータ処理、センサーデータの管理、コンテンツ管理システムなど、さまざまな場面で活用されています。また、情報の柔軟な更新が求められる場合や、異なるデータタイプを統合して管理する必要がある場合にもNoSQLは有用です。 NoSQLデータベースは、特にスケーラビリティやパフォーマンスが求められるプロジェクトに適しています。横方向のスケーリングが容易であり、データを追加することでシステム全体の性能を向上させることができます。また、スキーマレスな設計が可能なため、事前にデータの構造を定義する必要がなく、アプリケーションの進化に柔軟に対応できます。これらの理由から、NoSQLはスタートアップ企業だけでなく、大企業でも広く採用されています。 関連技術としては、ビッグデータ処理フレームワークや分散システムの知識が挙げられます。例えば、Apache HadoopやApache Sparkといったビッグデータ分析ツールは、NoSQLデータベースと組み合わせて使われることが多いです。これにより、大量のデータを効率的に処理し、価値ある情報を抽出することが可能になります。また、コンテナ技術やマイクロサービスアーキテクチャとも相性が良く、アプリケーション全体の柔軟性を高めることができます。 さらに、NoSQLデータベースはクラウド環境での利用も増えており、クラウドプロバイダが提供するマネージドサービスを活用することで、インフラの管理を簡素化できます。これにより、開発者はデータベースの構築や運用にかかる時間を削減し、より早くアプリケーションの開発に集中することができます。 まとめると、NoSQLは従来のリレーショナルデータベースとは異なる柔軟なデータストレージ手法を提供し、多様なデータ形式や大規模なデータの処理に適しています。さまざまな種類のNoSQLデータベースが存在し、それぞれの特性を活かして幅広い用途で使用されています。また、関連技術と組み合わせることで、より効率的なデータ管理と分析が可能になります。NoSQLは今後ますます重要な役割を果たしていくでしょう。 |
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